Biclustering of data matrices in systems biology via optimal re-ordering

Peter A. DiMaggio, Scott R. McAllister, Christodoulos A. Floudas, Xiao Jiang Feng, Joshua D. Rabinowitz, Herschel A. Rabitz

Research output: Chapter in Book/Report/Conference proceedingChapter


In this work we present an optimal method for the biclustering data matrices in systems biology. Our approach is based on the iterative optimal re-ordering of submatrices to generate biclusters. A network flow model is presented for performing the row and column permutations for a specified objective function, which is general enough to accommodate many different metrics. The proposed biclustering approach is applied to a set of metabolite concentration data and we demonstrate that our methods arranges the metabolites in an order which more closely reflects their known metabolic functions and has the ability to classify related objects into groups.

Original languageEnglish (US)
Title of host publication18th European Symposium on Computer Aided Process Engineering
EditorsBertrand Braunschweig, Xavier Joulia
Number of pages6
StatePublished - 2008

Publication series

NameComputer Aided Chemical Engineering
ISSN (Print)1570-7946

All Science Journal Classification (ASJC) codes

  • General Chemical Engineering
  • Computer Science Applications


  • Mixed-integer linear programming (MILP)
  • biclustering
  • network flow
  • rearrangement clustering


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